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使用 JavaScript 编写 Atlas Functions

您将使用上下文对象编写 Atlas Functions，以访问关联服务、环境变量和内置 MongoDB 客户端。

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使用 JavaScript 编写 Atlas Functions 是 CoddyKit 上的免费 MongoDB Academy 课时。这是第 3 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 MongoDB Academy 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 MongoDB Academy 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

What Are Atlas Functions?

Atlas Functions are server-side JavaScript functions that run in the Atlas App Services managed runtime. They are the execution unit behind database triggers, scheduled triggers, and HTTPS endpoints. Functions have full access to the MongoDB client, environment variables, linked third-party services (HTTP, AWS, Twilio, etc.), and can call other Atlas Functions.

Function Anatomy: exports and context

Every Atlas Function exports a single async function as its entry point via exports = async function(...args) {}. Inside the function, the global context object provides access to Atlas services. The function receives arguments that vary by invocation type: database triggers receive a change event, HTTPS endpoints receive an HTTP request, and called functions receive the arguments passed by the caller.

// Minimal Atlas Function structure
exports = async function(arg1, arg2) {
  // context is globally available
  const db = context.services.get('mongodb-atlas').db('mydb')
  const result = await db.collection('users').findOne({ _id: arg1 })
  return result
}

Accessing MongoDB With context.services

context.services.get('mongodb-atlas') returns a MongoDB client bound to your linked Atlas cluster. From it you get a database handle and then a collection handle — the same API as the Node.js MongoDB driver. Operations are async and should be awaited. The client is pre-configured with the App Services internal credentials, so you do not manage connection strings in function code.

exports = async function() {
  // Get the linked MongoDB service
  const mongodb = context.services.get('mongodb-atlas')
  const db = mongodb.db('mydb')
  const orders = db.collection('orders')

  // Full CRUD API available
  const pending = await orders.find({ status: 'pending' }).toArray()
  await orders.updateMany({ status: 'pending' }, { $set: { notified: true } })

  return { processed: pending.length }
}

Environment Variables: context.values and context.environment

Hardcoding secrets (API keys, passwords) in function code is dangerous. Atlas Functions support two mechanisms for secure config: Values — static strings or secrets stored in App Services and accessed via context.values.get('myValue'). Environment variables — per-environment overrides accessed via context.environment.values.MY_VAR. Use these to store API keys, webhook secrets, and environment-specific settings.

exports = async function() {
  // Retrieve a stored secret (never exposed in function logs)
  const apiKey = context.values.get('STRIPE_SECRET_KEY')

  // Or use environment-specific values
  const webhookUrl = context.environment.values.SLACK_WEBHOOK_URL

  // Use in an HTTP call
  const http = context.services.get('myHTTP')
  await http.post({
    url: webhookUrl,
    headers: { 'Content-Type': ['application/json'] },
    body: JSON.stringify({ text: 'Job complete' })
  })
}

Making HTTP Requests

Atlas Functions can call external REST APIs using a linked HTTP service or the built-in context.http shortcut. This enables integrations with Stripe, SendGrid, Slack, Twilio, GitHub, and any other REST API without deploying additional infrastructure. Always store API keys in Values or Secrets, never in code.

exports = async function(orderId, amount) {
  // Create a Stripe payment intent via REST API
  const stripeKey = context.values.get('STRIPE_SECRET_KEY')
  const response = await context.http.post({
    url: 'https://api.stripe.com/v1/payment_intents',
    headers: {
      'Authorization': ['Bearer ' + stripeKey],
      'Content-Type': ['application/x-www-form-urlencoded']
    },
    body: 'amount=' + Math.round(amount * 100) + '&currency=usd&metadata[orderId]=' + orderId
  })

  const body = EJSON.parse(response.body.text())
  return body.client_secret
}

Calling Other Atlas Functions

Atlas Functions can call each other with context.functions.execute('functionName', arg1, arg2). This promotes reuse — you can write utility functions (send an email, log an event, validate a JWT) once and call them from any trigger or endpoint function. Recursive calls are supported but Atlas limits call depth to prevent infinite recursion.

// Main function calls a utility function
exports = async function(userId) {
  const db = context.services.get('mongodb-atlas').db('mydb')
  const user = await db.collection('users').findOne({ _id: userId })

  // Call a reusable 'sendWelcomeEmail' function
  await context.functions.execute('sendWelcomeEmail', user.email, user.name)

  return { status: 'welcome email sent' }
}

User Context: Who Is Calling?

In functions called by authenticated users (via HTTPS endpoints with user authentication), context.user provides the caller's identity: their user ID, email, roles, and custom data. This lets you build secure, user-scoped logic without passing user IDs manually. Functions invoked by triggers or scheduled jobs have a system-level user context.

// HTTPS endpoint function that is user-scoped
exports = async function({ query, body }) {
  // context.user is populated when the endpoint uses user auth
  const currentUserId = context.user.id
  const db = context.services.get('mongodb-atlas').db('mydb')

  // Users can only read their own data
  const orders = await db.collection('orders')
    .find({ ownerId: currentUserId })
    .toArray()

  return { orders }
}

Error Handling Best Practices

Wrap your function body in try/catch and always re-throw errors after logging them. This ensures Atlas marks the invocation as failed (enabling retry logic for triggers) and the error appears in the execution log with full context. Use structured logging (JSON strings) rather than plain text so logs are machine-parseable.

exports = async function(payload) {
  const start = Date.now()
  try {
    const result = await processPayload(payload)
    console.log(JSON.stringify({ status: 'ok', result, ms: Date.now() - start }))
    return result
  } catch (err) {
    console.error(JSON.stringify({
      status: 'error',
      message: err.message,
      stack: err.stack,
      ms: Date.now() - start
    }))
    throw err  // re-throw so Atlas marks this invocation as FAILED
  }
}

Function Execution Limits

Atlas Functions have important execution limits: Maximum runtime: 90 seconds per invocation. Memory: 256 MB. Code size: 64 KB per function. Response size: 4 MB for HTTPS endpoints. For long-running or memory-intensive operations, design your functions to process data in small batches and use multiple invocations (via scheduled triggers) to handle large datasets.

Testing Functions Locally With app-services-cli

You can develop and test Atlas Functions locally using the Atlas App Services CLI (app-services-cli). Push your function code, trigger configurations, and environment values to App Services with a single command. The CLI also supports pulling your existing configuration as code so you can version-control it in Git alongside your application code.

// Install the App Services CLI
// npm install -g atlas-app-services-cli

// Pull existing config
// appservices pull --remote=<app_id>

// Push updated functions
// appservices push --include-node-modules

// Run a function locally (using App Services CLI)
// appservices function run --name=myFunction --arg='{"key":"val"}'

Function Naming and Organisation

As your App Services application grows, organise functions with consistent naming conventions. Use prefixes or folders: trigger_onOrderInsert, util_sendEmail, api_getProducts. Keep functions small and focused — a function that does one thing is easier to test, debug, and reuse. Extract shared logic into utility functions and call them with context.functions.execute() from multiple callers.

// Organised function naming examples:
// trigger_onOrderInsert  — database trigger handler
// trigger_dailyArchive   — scheduled trigger
// api_getOrders          — HTTPS endpoint handler
// util_sendEmail         — shared email utility
// util_validatePayload   — shared validation utility

// Calling a utility from any other function:
await context.functions.execute('util_sendEmail', {
  to: user.email,
  subject: 'Your order is confirmed',
  body: 'Order ID: ' + orderId
})

Quick Check

Test your understanding of MongoDB & NoSQL Databases concepts from this lesson.

在交互式课程中回答

Lesson Recap

In this lesson you learned: Atlas Functions export a single async function entry point and access MongoDB, HTTP services, and environment config through the global context object, functions can call each other with context.functions.execute() for reusable utility logic, and always re-throw errors after logging so Atlas marks invocations as failed and retries triggers appropriately. Next up we expose Atlas Functions as HTTPS endpoints.

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常见问题解答

「使用 JavaScript 编写 Atlas Functions」课时是免费的吗？

是的 — 「使用 JavaScript 编写 Atlas Functions」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 MongoDB Academy 课程的其余内容，请升级到 CoddyKit PRO。 MongoDB Academy 课程共包含 4 节课。

「使用 JavaScript 编写 Atlas Functions」这节课中我会学到什么？

您将使用上下文对象编写 Atlas Functions，以访问关联服务、环境变量和内置 MongoDB 客户端。你通过在浏览器中直接运行的动手代码来练习 MongoDB Academy，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

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无需任何先前经验。CoddyKit 上的 MongoDB Academy 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 3 节课，共 4 节。

「使用 JavaScript 编写 Atlas Functions」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

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